CN103399327A - Beidou system-based satellite signal optimizing system and method - Google Patents

Abstract

A satellite signal optimization system and method based on the Beidou system, the system includes a host computer, an intelligent obstacle avoidance car, a passive Beidou system, an antenna attitude control system, a power supply system and a monitoring system; the passive Beidou system includes a Beidou receiving antenna, Radio frequency module, FPGA and DSP, antenna attitude control system comprises drive module, ultrasonic sensor and ARM processor; Power supply system comprises solar battery group and solar battery controller, monitoring system comprises monitoring equipment, transmission equipment and display equipment, system of the present invention The method and the method have the characteristics of high energy utilization efficiency and good signal quality for searching satellites. The signal optimization algorithm is used to predict the state parameters of the system operation and the quality parameters of satellite signals to overcome the shortcomings of unstable satellite signals and lagging control command execution. The combination of the movable car based on radar laser and the Beidou receiving antenna can intelligently Track high-quality satellite signals and improve the quality of received satellite signals.

Description

A Beidou system-based satellite signal optimization system and method

technical field

The invention belongs to the technical field of electronic information, and in particular relates to a satellite signal optimization system and method based on the Beidou system.

Background technique

Satellite navigation and positioning systems have an important impact on economic development, social benefits and military fields. Our country attaches great importance to the construction and development of satellite navigation and positioning systems, and has been working hard to explore and research. "Beidou Satellite Navigation and Positioning System" (referred to as "Beidou System") is a satellite navigation and positioning system that can cover the whole world developed by my country's Baixing and operates independently. It is currently in the networking stage. The system has been successfully applied in many fields such as surveying and mapping, communication, transportation, public safety and disaster reduction and relief, bringing significant economic and social benefits.

As a new satellite navigation and positioning system, "Beidou System" has obvious technical advantages, but it also has certain application defects and deficiencies. Among them, the most prominent defect is the instability of the "Beidou system" signal. It often happens that the Beidou receiving antenna cannot find a signal in a certain period of time or in a certain direction, or the quality of the signal found is particularly poor. A stable signal is the prerequisite and guarantee for the good application of the Beidou system. At present, there is no good technology to solve the problem of signal instability of the "Beidou system". This problem is one of the important factors restricting the development of the "Beidou system". It should be highly valued and corresponding countermeasures should be taken to solve it.

Contents of the invention

Aiming at the problems existing in the prior art, the present invention provides a satellite signal optimization system based on the Beidou system, including a host computer, an intelligent obstacle avoidance car, a passive Beidou system, an antenna attitude control system, a power supply system and a monitoring system;

The intelligent obstacle avoidance car includes a motor drive module, a steering gear drive module, a laser radar module and a motion control module. The output end of the laser radar module is connected to the input end of the motion control module, and the different output ends of the motion control module are respectively connected to the input of the motor drive module. terminal and the input terminal of the steering gear drive module;

The passive Beidou system includes a Beidou receiving antenna, a radio frequency module, an FPGA and a DSP, the Beidou receiving antenna is fixedly installed on the intelligent obstacle avoidance car, the output of the Beidou receiving antenna is connected to the input of the radio frequency module, and the output of the radio frequency module is connected to the FPGA The input end of the FPGA, the output end of the FPGA is connected to the input end of the DSP;

The antenna attitude control system includes a drive module, an ultrasonic sensor and an ARM processor; an output end of the DSP is connected to an input end of the ARM processor, and two different output ends of the ARM processor are respectively connected to an input end of the upper computer and the drive module, The output end of the drive module is connected to the input end of the Beidou receiving antenna, and the output end of the ultrasonic sensor used to detect the pitch angle and azimuth state of the Beidou receiving antenna is connected to the input end of the ARM processor;

The power supply system includes a solar cell group and a solar cell controller, each solar cell in the solar cell group is connected in parallel, the solar cell controller is connected to the solar cell group, and an input end of the solar cell controller is connected to an output end of the DSP;

The intelligent obstacle avoidance car, the passive Beidou system, and the antenna attitude control system are all powered by the power supply system, and the output ends of each solar cell in the solar battery pack are respectively connected to the intelligent obstacle avoidance car, the passive Beidou system, and the antenna attitude control system;

The monitoring system includes a monitoring device, a transmission device and a display device. The monitoring device is placed within the environment range of the movement of the intelligent obstacle avoidance car, and the output end of the monitoring device is connected to the display device through the transmission device.

The method for performing satellite signal optimization using the satellite signal optimization system based on the Beidou system includes the following steps:

Step 1: DSP judges whether the power supply of the intelligent obstacle avoidance car, passive Beidou system, antenna attitude control system and monitoring system is normal: if yes, go to step 3; if not, go to step 2;

Step 2: Use the solar battery controller to control the solar battery to supply power to the intelligent obstacle avoidance car, passive Beidou system, antenna attitude control system and monitoring system;

Step 3: During the movement of the intelligent obstacle avoidance car, the laser radar module is used to detect the obstacles in the moving environment of the car in real time, so as to realize the intelligent obstacle avoidance during the movement of the intelligent obstacle avoidance car. At the same time, the monitoring system monitors the movement process of the intelligent obstacle avoidance car in real time ;

Step 4: The Beidou receiving antenna receives the current satellite signal in real time, and sends the satellite signal to the FPGA through the RF module;

Step 5: The FPGA demodulates and despreads the satellite signal, and transmits the demodulated and despreaded signal to the DSP;

Step 6: The DSP performs positioning calculation and time correction on the received signal to complete the timing, and transmits the timing information to the ARM processor for storage. At the same time, the ultrasonic sensor collects the pitch angle and azimuth status of the Beidou receiving antenna at the current moment The information is transmitted to the ARM processor for storage;

The timing information includes the current position information, current time information and signal strength information of the intelligent obstacle avoidance car;

Step 7: The ARM processor sends the saved timing information and the current pitch angle and azimuth status information of the Beidou receiving antenna to the host computer;

Step 8: The ARM processor uses the signal optimization learning algorithm to predict the possible range of the optimal satellite signal at the next moment, and then find the optimal satellite signal;

Specific steps are as follows:

Step 8.1: The ARM processor normalizes the received timing information at each moment and the corresponding pitch angle and azimuth status information of the Beidou receiving antenna;

Step 8.2: Use the normalized data as sample data for signal optimization learning;

Step 8.3: Predict the possible range of the optimal satellite signal at the next moment according to the sample data learned by signal optimization;

Step 8.3.1: Set the satellite signal search range, signal congestion factor, signal strength threshold, maximum number of searches and stagnation parameters;

The stagnation parameter refers to the number of times the signal strength threshold has been exceeded for multiple consecutive times during the process of searching for satellite signals;

Step 8.3.2: Search the sample data for signal optimization learning. If during the process of searching for satellite signals, the satellite signal strength within a certain range exceeds the signal strength threshold for several times consecutively, and the number of times reaches the stagnation parameter, then the range is down. For the possible range of the optimal satellite signal at a moment, go to step 8.4; otherwise, go to step 8.3.3;

Step 8.3.3: Judging whether the number of searches of the sample data of the current signal optimization learning has reached the maximum number of searches, if yes, perform step 8.3.4, otherwise continue to search;

Step 8.3.4: Compare the signal strength of each satellite signal within the satellite signal search range, and transmit the optimal satellite signal strength to the DSP. The signal strength information, the current position information of the corresponding satellite and the current time information form timing information, respectively Send to the ARM processor and host computer, perform step 8.1;

Step 8.4: Use the neural network algorithm to conduct network learning on the optimal satellite signal within the possible range of the optimal satellite signal at the next moment, and obtain the predicted value of the optimal satellite signal strength at the next moment, that is, find the optimal satellite Signal;

Step 9: The ARM processor sends the signal strength of the found optimal satellite signal and the position information of the position point corresponding to the signal strength to the drive module in the antenna attitude control system and the motion control module of the intelligent obstacle avoidance car;

The position information of the position point corresponding to the signal strength is converted into the position information of the intelligent obstacle avoidance car and the pitch angle and azimuth state information of the Beidou receiving antenna, and the position information of the intelligent obstacle avoidance car is sent to the motion control module of the intelligent obstacle avoidance car, The pitch angle and azimuth state information of the Beidou receiving antenna are sent to the drive module in the antenna attitude control system;

Step 10: The motion control module of the smart obstacle avoidance car controls the movement of the smart obstacle avoidance car within the possible range of the optimal satellite signal;

Step 11: The drive module in the antenna attitude control system adjusts the attitude of the Beidou receiving antenna according to the received information, so that the receiving direction of the Beidou receiving antenna is the best within the range where the optimal satellite signal may appear;

Step 12: When the Beidou receiving antenna receives the satellite signal, the DSP transmits the timing information of the satellite signal to the ARM processor for storage;

Step 13: The ARM processor uploads the status parameters of the current system operation to the host computer. The status parameters include: the possible range of the optimal satellite signal at the next moment predicted by the signal optimization algorithm and the current optimal satellite signal timing information;

Step 14: The operator can control the satellite signal optimization system in real time according to the status parameters of the current system operation received by the host computer. When the system power supply is abnormal, the operator can send a control command to the DSP through the host computer to control the solar battery to the system. power supply.

Beneficial effect:

The Beidou-based intelligent signal receiving antenna system of the present invention has the characteristics of high energy utilization efficiency, good signal quality for searching satellites, and stable system operation. Compared with the traditional "Beidou system" signal receiving device, due to the use of solar cells as the main power source, the energy utilization rate of this system is about 15% higher than that of the traditional system. The system adopts an integrated integrated control system composed of FPGA and DSP microprocessor to effectively control each module, and uses signal optimization algorithm to predict the state parameters of the system operation and the quality parameters of satellite signals, which overcomes the instability of satellite signals, The shortcomings of the lag in the execution of control commands, the combination of the radar laser-based movable car and the Beidou receiving antenna has broken through the traditional receiving antenna technology, changing from passive receiving mode to active searching mode, which can intelligently track high-quality satellite signals, greatly improving The quality of the received satellite signal and the stability of the system operation are guaranteed.

Description of drawings

Fig. 1 is the overall system structural diagram of the specific embodiment of the present invention;

Fig. 2 is the control schematic diagram of the steering gear drive module of the specific embodiment of the present invention;

Fig. 3 is a control schematic diagram of a motion control module according to a specific embodiment of the present invention;

Fig. 4 is a schematic diagram of a signal modulation circuit of a specific embodiment of the present invention;

Fig. 5 is a schematic diagram of a triangular wave disturbance signal generating circuit of a specific embodiment of the present invention;

Fig. 6 is a flow chart of a satellite signal optimization method based on the Beidou system according to a specific embodiment of the present invention;

Fig. 7 is a flowchart of a signal optimization algorithm in a specific embodiment of the present invention.

Detailed ways

The specific implementation manners of the present invention will be described in detail below in conjunction with the accompanying drawings.

As shown in Figure 1, the satellite signal optimization system based on the Beidou system in this embodiment includes a host computer, an intelligent obstacle avoidance car, a passive Beidou system, an antenna attitude control system, a power supply system, and a monitoring system;

The intelligent obstacle avoidance car includes a motor drive module, a steering gear drive module, a laser radar module and a motion control module. The output end of the laser radar module is connected to the input end of the motion control module, and the different output ends of the motion control module are respectively connected to the input of the motor drive module. terminal and the input terminal of the steering gear drive module. The environment around the intelligent obstacle avoidance car is detected by the laser radar sensor, and the signal is transmitted to the motion control module according to the detected signal. The motion control module controls the motor drive module and the steering gear drive module according to the signal to realize the intelligent obstacle avoidance car. The forward, backward, and turning movements of the robot can smoothly avoid obstacles.

The motor drive module uses a DC motor to provide power for the movement of the intelligent obstacle avoidance car at various speeds. This module composes the power triode into an H-bridge motor drive circuit, and uses PWM waves to control the effective value and polarity of the output voltage. This speed regulation method has excellent speed regulation characteristics, smooth adjustment, and wide speed regulation range. , large overload capacity, can withstand frequent load shocks, low energy consumption, etc., and can also achieve frequent stepless quick start and reverse.

The steering gear drive module is installed on the connecting rod of the front wheel (steering wheel) of the smart obstacle avoidance car. The vertical rotation of the steering gear drive module is converted into the rotation of the connecting rod, and then drives the front wheel to turn left and right. The steering gear drive module is a position servo driver. Its working principle is: the control signal is compared with the servo position feedback signal to obtain a DC bias voltage, and the bias voltage enters the signal modulation chip to generate a comparison level, which is passed through the PWM control chip. After the UC1637, it outputs a PWM signal with a certain duty cycle to drive the on-off of the IGBT in the IPM circuit, so as to realize the position control of the electric steering gear. The control principle of the steering gear driving module is shown in Figure 2.

The laser radar module is equivalent to a sensor. The module is installed on a DC motor (motor drive module) with an encoder. The laser radar measures the distance and the encoder measures the angle. In this way, the DC motor drives the laser radar module to rotate for one revolution to build a surrounding area. environmental information.

The motion control module adopts MCUMB95F506 controller of Foxconn's FM3 (FujitsuArm-cortesm3) series. The high-precision sampling makes the motor control more precise. The 3-unit 12-bit A/D of the controller has as many as 16 channels, which can improve the position accuracy and the precision of motor control. The MCUMB95F506 communicates with the motor drive module, the steering gear drive module and the laser radar module through different I/O pins. For the fast, stable and correct movement of the obstacle avoidance car, the control principle of MCUMB95F506 is shown in Figure 3. When an obstacle is detected, the steering gear drive module controls the intelligent obstacle avoidance car to turn, otherwise it will move forward at the same speed and in the forward process When there is a deviation from the traveling track, the motor drive module will adjust the deceleration, otherwise it will continue to move forward at the original speed until it detects that the intelligent obstacle avoidance car reaches the end point and stops moving.

The passive Beidou system includes the Beidou receiving antenna, RF module, FPGA and DSP. The Beidou receiving antenna is fixedly installed on the smart obstacle avoidance car. The output of the Beidou receiving antenna is connected to the input of the RF module, and the output of the RF module is connected to the input of the FPGA. The output end of the FPGA is connected to the input end of the DSP;

The passive Beidou system is based on the "Beidou No. 1" system, and achieves positioning and timing functions in a passive manner. The Beidou receiving antenna module uses an external antenna. The Beidou receiving antenna model is DY-BDTRT06P00A. The antenna is a right-handed polarized ceramic medium , The Beidou receiving antenna module includes: ceramic antenna, low-noise signal module, cables and connectors. The radio frequency module adopts the radio frequency module of Aeroflex3030PXI series, which can perform frequency conversion sampling of radio frequency signals with high precision and high dynamic range.

The passive Beidou system of this embodiment adopts FPGA and DSP for data processing. FPGA adopts EP2C35F484 of Altera Company, which realizes asynchronous communication with the radio frequency module through UART; DSP adopts TMS320VC5509A of TI Company. The EMIF signal lines of the DSP are all connected to the FPGA to realize the transmission of information between the two.

The antenna attitude control system includes a drive module, an ultrasonic sensor and an ARM processor; the output end of the DSP is connected to the input end of the ARM processor, and the two different output ends of the ARM processor are respectively connected to the upper computer and the input end of the drive module. The output end is connected to the input end of the Beidou receiving antenna, and the output end of the ultrasonic sensor used to detect the pitch angle and azimuth state of the Beidou receiving antenna is connected to the input end of the ARM processor.

The model of the ultrasonic sensor is SIEMENS 3RG6024-3ACOO, and the drive module adopts the drive chip L298N developed by SGS (China Standard Technical Service Co., Ltd.). This module can provide power for the movement of the Beidou receiving antenna to realize the 360-degree freedom of the Beidou receiving antenna Turn without hassle.

The ARM processor includes the ARM Cortex A9 processor and its peripheral modules. The ARM Cortex A9 processor is embedded with a satellite signal optimization algorithm to control the attitude of the Beidou receiving antenna, so as to realize the automatic optimization and real-time tracking of the Beidou receiving antenna, ensuring that the satellite signal is optimized at every moment. It can feed back the optimal signal of the satellite to the DSP of the passive Beidou system and complete the timing task. The ARM processor communicates with the DSP through a dual-port serial port. The peripheral module of the ARM processor includes a voltage and current sampling conversion module, a signal modulation circuit, a triangular wave disturbance signal generation circuit, a register module and a communication module. The voltage and current sampling conversion module includes a voltage sensor. and the current sensor, the principle of the signal modulation circuit is shown in Figure 4, and the principle of the triangular wave disturbance signal generation circuit is shown in Figure 5. The register module mainly stores the operating state parameters of the system. The IS61LV16416 type memory is selected. Pins 41, 17, and 6 of the memory circuit are connected to pins 42, 84, and 33 of the ARM processor chip. The communication module adopts the MAX485 chip, which is mainly responsible for the communication between the ARM processor and the upper computer. The chip adopts the RS485 protocol to establish the communication protocol between the ARM processor and the upper computer. The upper computer is connected to the SCI/RXD, PC2, SCI/TXD pins of the ARM Cortex A9 processor through the pins RO, RE, and DI of the communication module MAX485, and the MAX485 socket is connected to the serial port of the upper computer through the signal line, and integrated through the ARM processor It has a communication function and can realize remote control.

The Beidou receiving antenna receives the current satellite signal in real time and transmits it to the FPGA for signal processing to obtain the demodulation and despreading of the satellite navigation message, and transmits the demodulated and despreaded signal to the DSP, and the DSP collects and processes the demodulated and despreaded signal. Realize positioning calculation and time correction value calculation, cooperate with FPGA to generate accurate second pulse, under the drive of second pulse, calculate the current time information, and transmit the information to ARM processor; ARM processor receives the time information, and ARM processes it The timing information and the pitch angle and azimuth status information of the Beidou receiving antenna at the current moment are sent to the host computer, and at the same time, it predicts the possible range of the optimal satellite signal at the next moment, and then finds the optimal satellite signal. The optimal satellite signal is fed back to the DSP to complete the timing, and finally the peripheral communication module of the DSP uploads the timing information of the optimal satellite signal to the upper computer and the ARM processor at the same time. The ARM processor transmits the information to the drive module, and the drive module responds to the analysis of the information to control the attitude of the Beidou receiving antenna, realize the 360-degree free and unobstructed rotation of the Beidou receiving antenna, and use the ultrasonic sensor to detect the pitch of the Beidou receiving antenna and orientation status, real-time feedback to DSP and sent to the host computer by ARM through the serial port.

The power supply system includes a solar cell group and a solar cell controller, each solar cell in the solar cell group is connected in parallel, the solar cell controller is connected with the solar cell group, and the input end of the solar cell controller is connected with an output end of the DSP; intelligent obstacle avoidance The car, the passive Beidou system, and the antenna attitude control system are all powered by the power supply system, and the output terminals of each solar cell in the solar battery pack are respectively connected to the intelligent obstacle avoidance car, the passive Beidou system, and the antenna attitude control system;

The power supply system converts solar energy into electrical energy and stores it, and acts as a supplementary power source when the electrical energy is in short supply. The solar battery controller controls the state of the solar battery. When the power supplied by the solar battery to each system is too high, the PWM wave is sent by the DSP to close the charging switch, and the solar battery acts as a DC load, absorbing excess power and storing it; otherwise, the discharging switch is closed, and the solar battery continues to supply power to each system.

The monitoring system includes monitoring equipment, transmission equipment and display equipment. The monitoring equipment adopts Siemens cameras. The equipment is placed in the environment range of the intelligent obstacle avoidance car. The output of the monitoring equipment is connected to the display equipment through the transmission equipment.

The monitoring equipment is placed near the intelligent obstacle avoidance car equipped with the Beidou receiving antenna to realize real-time monitoring of the movement of the Beidou receiving antenna and the intelligent obstacle avoidance car. The transmission device adopts optical fiber, and the video signal output by the monitoring device is transmitted to the display device through optical fiber transmission. The display equipment includes hard disk video recording system, video matrix, picture processor, switcher and distributor remote expansion system, which can observe the status of the Beidou receiving antenna and the operation of the intelligent obstacle avoidance car in real time.

In this embodiment, the satellite signal optimization system based on the Beidou system is placed on the roof platform of a high-rise building, and the above-mentioned satellite signal optimization system based on the Beidou system is used to perform satellite signal optimization, as shown in Figure 6, including The following steps:

Step 1: DSP judges whether the power supply of the intelligent obstacle avoidance car, passive Beidou system, antenna attitude control system and monitoring system is normal: if yes, go to step 3; if not, go to step 2;

Step 2: Use the solar battery controller to control the solar battery to supply power to the intelligent obstacle avoidance car, passive Beidou system, antenna attitude control system and monitoring system;

The solar cell converts solar energy into electric energy and stores it, and acts as a supplementary power source when the electric energy is in short supply, and the solar cell controller controls the state of the solar cell. When the power supplied by the solar battery to each system is too high, the PWM wave is sent out by the DSP to close the charging switch, and the solar battery acts as a DC load to absorb excess power and store it; otherwise, the discharge switch is closed, and the solar battery continues to supply power to each system.

Step 3: During the movement of the intelligent obstacle avoidance car, the laser radar module is used to detect the obstacles in the moving environment of the car in real time, so as to realize the intelligent obstacle avoidance during the movement of the intelligent obstacle avoidance car. At the same time, the monitoring system monitors the movement process of the intelligent obstacle avoidance car in real time ;

Step 4: The Beidou receiving antenna receives the current satellite signal in real time, and sends the satellite signal to the FPGA through the RF module;

Step 5: The FPGA demodulates and despreads the satellite signal, and transmits the demodulated and despreaded signal to the DSP;

Step 6: The DSP performs positioning calculation and time correction on the received signal to complete the timing, and transmits the timing information to the ARM processor for storage. At the same time, the ultrasonic sensor collects the pitch angle and azimuth status of the Beidou receiving antenna at the current moment The information is transmitted to the ARM processor for storage;

The timing information includes the current location information, current time information and signal strength information of the intelligent obstacle avoidance car;

Step 7: The ARM processor sends the saved timing information and the current pitch angle and azimuth status information of the Beidou receiving antenna to the host computer;

Step 8: The ARM processor uses the signal optimization learning algorithm to predict the possible range of the optimal satellite signal at the next moment, and then find the optimal satellite signal;

The signal optimization learning algorithm is obtained by improving the basic artificial fish swarm algorithm in the prior art. As shown in Figure 7, the ARM processor uses the signal optimization learning algorithm to calculate the possible range of the optimal satellite signal at the next moment. Prediction, and then find the specific steps of the optimal satellite signal as follows:

Step 8.1: The ARM processor normalizes the received timing information at each moment and the corresponding pitch angle and azimuth status information of the Beidou receiving antenna;

Step 8.2: Use the normalized data as sample data for signal optimization learning;

Step 8.3: Predict the possible range of the optimal satellite signal at the next moment according to the sample data learned by signal optimization;

Step 8.3.1: Set the satellite signal search range, signal congestion factor, signal strength threshold, maximum number of searches and stagnation parameters;

The stagnation parameter refers to the number of times the signal strength threshold has been exceeded for multiple consecutive times during the process of searching for satellite signals;

Step 8.3.2: Search the sample data for signal optimization learning. If during the process of searching for satellite signals, the satellite signal strength within a certain range exceeds the signal strength threshold for several times consecutively, and the number of times reaches the stagnation parameter, then the range is down. For the possible range of the optimal satellite signal at a moment, go to step 8.4; otherwise, go to step 8.3.3;

Step 8.3.3: Judging whether the number of searches of the sample data of the current signal optimization learning has reached the maximum number of searches, if yes, perform step 8.3.4, otherwise continue to search;

Step 8.3.4: Compare the signal strength of each satellite signal within the satellite signal search range, and transmit the optimal satellite signal strength to the DSP. The signal strength information, the current position information of the corresponding satellite and the current time information form timing information, respectively Send to the ARM processor and host computer, perform step 8.1;

Step 8.4: Learn the optimal satellite signal within the possible range of the optimal satellite signal at the next moment, and obtain the predicted value of the optimal satellite signal strength at the next moment, that is, find the optimal satellite signal;

The learning rule of the signal optimization algorithm is: the current state of a satellite signal point is X _i , and a satellite signal is randomly selected within the possible range of the optimal satellite signal (that is, d _ij ≤ VISUAL), and its state is X _j , when the When the strength of the random satellite signal is greater than the strength of the current satellite signal, take a step forward in the direction of the random satellite signal; otherwise, randomly select the satellite signal again to determine whether the above advance condition is met; after repeated several times, if the advance condition is still not met, then randomly Moving one step further, the learning rule is expressed as follows:

d _ij ≤ VISUAL:

$\left\{\begin{array}{ccc}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; inextk</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; ik</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; Random</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}<span\; class="notranslate">\; )</span>& <span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; jk</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; ik</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; /</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; |</span>& {\mathrm{<span\; class="notranslate">\; FC</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; ></span>{\mathrm{<span\; class="notranslate">\; FC</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\\ {\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; inextk</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; ik</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; Random</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&Delta;</span>}<span\; class="notranslate">\; )</span>& & {\mathrm{<span\; class="notranslate">\; FC</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; FC</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\end{array}\right.$

in:

d _ij ＝||X _i -X _j ||——the distance between two adjacent searched satellite signal points, that is, the two-norm of the vector (X _i -X _j );

VISUAL——Satellite signal search range, that is, the range where the optimal satellite signal may appear;

X=(x ₁ , x ₂ ,..., x _i )——the state vector of each signal point of the satellite signal, where x _i is the control variable for optimization;

x _jk ——the kth parameter of the state vector X _j ;

x _ik ——the kth parameter of the state vector _Xi ;

Random(Δ)——a random number between [0, Δ];

Δ——the difference between the strongest and weakest signals when searching for satellite signals;

FC _i - current received satellite signal strength;

FC _j ——satellite signal strength for the next random search;

Step 9: The ARM processor sends the signal strength of the found optimal satellite signal and the position information of the position point corresponding to the signal strength to the drive module in the antenna attitude control system and the motion control module of the intelligent obstacle avoidance car;

The position information of the position point corresponding to the signal strength is converted into the position information of the intelligent obstacle avoidance car and the pitch angle and azimuth state information of the Beidou receiving antenna, and the position information of the intelligent obstacle avoidance car is sent to the motion control module of the intelligent obstacle avoidance car, The pitch angle and azimuth state information of the Beidou receiving antenna are sent to the drive module in the antenna attitude control system;

Step 10: The motion control module of the smart obstacle avoidance car controls the movement of the smart obstacle avoidance car within the possible range of the optimal satellite signal;

Step 11: The drive module in the antenna attitude control system adjusts the attitude of the Beidou receiving antenna according to the received information, so that the receiving direction of the Beidou receiving antenna is the best within the range where the optimal satellite signal may appear;

Step 12: When the Beidou receiving antenna receives the satellite signal, the DSP transmits the timing information of the satellite signal to the ARM processor for storage;

Step 13: The ARM processor uploads the status parameters of the current system operation to the host computer. The status parameters include: the possible range of the optimal satellite signal at the next moment predicted by the signal optimization algorithm and the current optimal satellite signal timing information;

Step 14: The operator can control the satellite signal optimization system in real time according to the status parameters of the current system operation received by the host computer. When the system power supply is abnormal, the operator can send a control command to the DSP through the host computer to control the solar battery to the system. power supply.

Claims (2)

1. A satellite signal optimization system based on the Beidou system, including a host computer and an intelligent obstacle avoidance car, the intelligent obstacle avoidance car includes a motor drive module, a steering gear drive module, a laser radar module and a motion control module, and a laser radar module The output end of the motion control module is connected to the input end of the motion control module, and the different output ends of the motion control module are respectively connected to the input end of the motor drive module and the input end of the steering gear drive module. It is characterized in that: the system also includes passive Beidou system, antenna attitude Control system, power supply system and monitoring system; The passive Beidou system includes a Beidou receiving antenna, a radio frequency module, an FPGA and a DSP, the Beidou receiving antenna is fixedly installed on the intelligent obstacle avoidance car, the output of the Beidou receiving antenna is connected to the input of the radio frequency module, and the output of the radio frequency module is connected to the FPGA The input end of the FPGA, the output end of the FPGA is connected to the input end of the DSP; The antenna attitude control system includes a drive module, an ultrasonic sensor and an ARM processor; an output end of the DSP is connected to an input end of the ARM processor, and two different output ends of the ARM processor are respectively connected to an input end of the upper computer and the drive module, The output end of the drive module is connected to the input end of the Beidou receiving antenna, and the output end of the ultrasonic sensor used to detect the pitch angle and azimuth state of the Beidou receiving antenna is connected to the input end of the ARM processor; The power supply system includes a solar cell group and a solar cell controller, each solar cell in the solar cell group is connected in parallel, the solar cell controller is connected to the solar cell group, and an input end of the solar cell controller is connected to an output end of the DSP; The intelligent obstacle avoidance car, the passive Beidou system, and the antenna attitude control system are all powered by the power supply system, and the output ends of each solar cell in the solar battery pack are respectively connected to the intelligent obstacle avoidance car, the passive Beidou system, and the antenna attitude control system; The monitoring system includes a monitoring device, a transmission device and a display device. The monitoring device is placed within the environment range of the movement of the intelligent obstacle avoidance car, and the output end of the monitoring device is connected to the display device through the transmission device. 2. adopt the method for satellite signal optimization based on the satellite signal optimization system of Beidou system according to claim 1, it is characterized in that: comprise the following steps: Step 1: DSP judges whether the power supply of the intelligent obstacle avoidance car, passive Beidou system, antenna attitude control system and monitoring system is normal: if yes, go to step 3; if not, go to step 2; Step 2: Use the solar battery controller to control the solar battery to supply power to the intelligent obstacle avoidance car, passive Beidou system, antenna attitude control system and monitoring system; Step 3: During the movement of the intelligent obstacle avoidance car, the laser radar module is used to detect the obstacles in the moving environment of the car in real time, so as to realize the intelligent obstacle avoidance during the movement of the intelligent obstacle avoidance car. At the same time, the monitoring system monitors the movement process of the intelligent obstacle avoidance car in real time ; Step 4: The Beidou receiving antenna receives the current satellite signal in real time, and sends the satellite signal to the FPGA through the RF module; Step 5: The FPGA demodulates and despreads the satellite signal, and transmits the demodulated and despreaded signal to the DSP; Step 6: The DSP performs positioning calculation and time correction on the received signal to complete the timing, and transmits the timing information to the ARM processor for storage. At the same time, the ultrasonic sensor collects the pitch angle and azimuth status of the Beidou receiving antenna at the current moment The information is transmitted to the ARM processor for storage; The timing information includes the current position information, current time information and signal strength information of the intelligent obstacle avoidance car; Step 7: The ARM processor sends the saved timing information and the current pitch angle and azimuth status information of the Beidou receiving antenna to the host computer; Step 8: The ARM processor uses the signal optimization learning algorithm to predict the possible range of the optimal satellite signal at the next moment, and then find the optimal satellite signal; Specific steps are as follows: Step 8.1: The ARM processor normalizes the received timing information at each moment and the corresponding pitch angle and azimuth status information of the Beidou receiving antenna; Step 8.2: Use the normalized data as sample data for signal optimization learning; Step 8.3: Predict the possible range of the optimal satellite signal at the next moment according to the sample data learned by signal optimization; Step 8.3.1: Set the satellite signal search range, signal congestion factor, signal strength threshold, maximum number of searches and stagnation parameters; The stagnation parameter refers to the number of times the signal strength threshold has been exceeded for multiple consecutive times during the process of searching for satellite signals; Step 8.3.2: Search the sample data for signal optimization learning. If during the process of searching for satellite signals, the satellite signal strength within a certain range exceeds the signal strength threshold for several times consecutively, and the number of times reaches the stagnation parameter, then the range is down. For the possible range of the optimal satellite signal at a moment, go to step 8.4; otherwise, go to step 8.3.3; Step 8.3.3: Judging whether the number of searches of the sample data of the current signal optimization learning has reached the maximum number of searches, if yes, perform step 8.3.4, otherwise continue to search; Step 8.3.4: Compare the signal strength of each satellite signal within the satellite signal search range, and transmit the optimal satellite signal strength to the DSP. The signal strength information, the current position information of the corresponding satellite and the current time information form timing information, respectively Send to the ARM processor and host computer, perform step 8.1; Step 8.4: Learn the optimal satellite signal within the possible range of the optimal satellite signal at the next moment, and obtain the predicted value of the optimal satellite signal strength at the next moment, that is, find the optimal satellite signal; Step 9: The ARM processor sends the signal strength of the found optimal satellite signal and the position information of the position point corresponding to the signal strength to the drive module in the antenna attitude control system and the motion control module of the intelligent obstacle avoidance car; The position information of the position point corresponding to the signal strength is converted into the position information of the intelligent obstacle avoidance car and the pitch angle and azimuth state information of the Beidou receiving antenna, and the position information of the intelligent obstacle avoidance car is sent to the motion control module of the intelligent obstacle avoidance car, The pitch angle and azimuth state information of the Beidou receiving antenna are sent to the drive module in the antenna attitude control system; Step 10: The motion control module of the smart obstacle avoidance car controls the movement of the smart obstacle avoidance car within the possible range of the optimal satellite signal; Step 11: The drive module in the antenna attitude control system adjusts the attitude of the Beidou receiving antenna according to the received information, so that the receiving direction of the Beidou receiving antenna is the best within the range where the optimal satellite signal may appear; Step 12: When the Beidou receiving antenna receives the satellite signal, the DSP transmits the timing information of the satellite signal to the ARM processor for storage; Step 13: The ARM processor uploads the status parameters of the current system operation to the host computer. The status parameters include: the possible range of the optimal satellite signal at the next moment predicted by the signal optimization algorithm and the current optimal satellite signal timing information; Step 14: The operator can control the satellite signal optimization system in real time according to the status parameters of the current system operation received by the host computer. When the system power supply is abnormal, the operator can send a control command to the DSP through the host computer to control the solar battery to the system. power supply.

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